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Full-Text Articles in Physical Sciences and Mathematics
To Hydrate Or Chlorinate: A Regression Analysis Of The Levels Of Chlorine In The Public Water Supply, Drew A. Doyle
To Hydrate Or Chlorinate: A Regression Analysis Of The Levels Of Chlorine In The Public Water Supply, Drew A. Doyle
HIM 1990-2015
Public water supplies contain disease-causing microorganisms in the water or distribution ducts. In order to kill off these pathogens, a disinfectant, such as chlorine, is added to the water. Chlorine is the most widely used disinfectant in all U.S. water treatment facilities. Chlorine is known to be one of the most powerful disinfectants to restrict harmful pathogens from reaching the consumer. In the interest of obtaining a better understanding of what variables affect the levels of chlorine in the water, this thesis will analyze a particular set of water samples randomly collected from locations in Orange County, Florida. Thirty water …
Contrails: Causal Inference Using Propensity Scores, Dean S. Barron
Contrails: Causal Inference Using Propensity Scores, Dean S. Barron
Journal of Modern Applied Statistical Methods
Contrails are clouds caused by airplane exhausts, which geologists contend decrease daily temperature ranges on Earth. Following the 2001 World Trade Center attack, cancelled domestic flights triggered the first absence of contrails in decades. Resultant exceptional data capacitated causal inference analysis by propensity score matching. Estimated contrail effect was 6.8981°F.
Predicting Successful Long-Term Weight Loss From Short-Term Weight-Loss Outcomes: New Insights From A Dynamic Energy Balance Model (The Pounds Lost Study), Diana Thomas, W Andrada Ivanescu, Corby K. Martin, Steven B. Heymsfield, Kaitlyn Marshall, Victoria E. Bodrato, Donald Williamson, Stephen Anton, Frank M. Sacks, Donna Ryan, George A. Bray
Predicting Successful Long-Term Weight Loss From Short-Term Weight-Loss Outcomes: New Insights From A Dynamic Energy Balance Model (The Pounds Lost Study), Diana Thomas, W Andrada Ivanescu, Corby K. Martin, Steven B. Heymsfield, Kaitlyn Marshall, Victoria E. Bodrato, Donald Williamson, Stephen Anton, Frank M. Sacks, Donna Ryan, George A. Bray
Department of Applied Mathematics and Statistics Faculty Scholarship and Creative Works
Background: Currently, early weight-loss predictions of long-term weight-loss success rely on fixed percent-weight-loss thresholds.
Objective: The objective was to develop thresholds during the first 3 mo of intervention that include the influence of age, sex, baseline weight, percent weight loss, and deviations from expected weight to predict whether a participant is likely to lose 5% or more body weight by year 1.
Design: Data consisting of month 1, 2, 3, and 12 treatment weights were obtained from the 2-y Preventing Obesity Using Novel Dietary Strategies (POUNDS Lost) intervention. Logistic regression models that included covariates of age, height, sex, baseline weight, …
The Number Of Subjects Per Variable Required In Linear Regression Analyses, Peter Austin, Ewout Steyerberg
The Number Of Subjects Per Variable Required In Linear Regression Analyses, Peter Austin, Ewout Steyerberg
Peter Austin
Objectives: To determine the number of independent variables that can be included in a linear regression model.
Study Design and Setting: We used a series of Monte Carlo simulations to examine the impact of the number of subjects per variable (SPV) on the accuracy of estimated regression coefficients and standard errors, on the empirical coverage of estimated confidence intervals, and on the accuracy of the estimated R2 of the fitted model.
Results: A minimum of approximately two SPV tended to result in estimation of regression coefficients with relative bias of less than 10%. Furthermore, with this minimum number of SPV, …